Practical notes on building software: delivery, reliability, and clean execution.
Establish clear ownership in AI teams by defining roles for prompt development, evaluation workflows, and incident response. Learn how to craft playbooks that ensure accountability and seamless collaboration.
Learn how to define clear quality metrics and cost models for AI-powered features in production. Explore monitoring strategies, performance trade-offs, and actionable steps to optimize ROI.
Early-stage founders must build reliability into their products from day one. Learn which processes to automate first—monitoring, testing, infrastructure provisioning, and backups—to scale confidently.
Explore best practices for designing tool-calling workflows in multi-step AI agents. Learn how to manage task decomposition, error handling, context management, and scalability for reliable automation.
Discover essential Retrieval-Augmented Generation (RAG) patterns to keep AI answers accurate and firmly grounded in your own documents. Master context chunking, semantic search, re-ranking, and more.
Discover how to reduce operational toil with AI-assisted workflows while maintaining safety and compliance. Learn actionable strategies to integrate AI tools, monitor outputs, and safeguard your systems.